An age estimation method using 3d-cnn from brain MRI images

Masaru Ueda, Koichi Ito, Kai Wu, Kazunori Sato, Yasuyuki Taki, Hiroshi Fukuda, Takafumi Aoki

研究成果: Conference contribution

12 被引用数 (Scopus)

抄録

A specific pattern of morphological changes in the human brain is observed during the process of brain development and healthy aging. The age of subjects can be estimated from brain images by evaluating such patterns. This paper proposes an age estimation method using 3-Dimensional Convolutional Neural Network (3D-CNN) from brain T1-weighted images so as to fully utilize the potential of volume data. Through a set of experiments using over 1,000 T1-weighted images of healthy Japanese, we demonstrate that the proposed method exhibits better performance on age estimation than the conventional methods using handcrafted local features and 2D-CNN.

本文言語English
ホスト出版物のタイトルISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging
出版社IEEE Computer Society
ページ380-383
ページ数4
ISBN(電子版)9781538636411
DOI
出版ステータスPublished - 2019 4
イベント16th IEEE International Symposium on Biomedical Imaging, ISBI 2019 - Venice, Italy
継続期間: 2019 4 82019 4 11

出版物シリーズ

名前Proceedings - International Symposium on Biomedical Imaging
2019-April
ISSN(印刷版)1945-7928
ISSN(電子版)1945-8452

Conference

Conference16th IEEE International Symposium on Biomedical Imaging, ISBI 2019
国/地域Italy
CityVenice
Period19/4/819/4/11

ASJC Scopus subject areas

  • 生体医工学
  • 放射線学、核医学およびイメージング

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